Definition
Benchmarks are standardized evaluation datasets and metrics used to measure AI model capabilities.
- **Popular LLM Benchmarks:**
- MMLU: Massive Multitask Language Understanding
- HumanEval: Code generation
- HellaSwag: Commonsense reasoning
- TruthfulQA: Truthfulness
- GSM8K: Grade school math
- MATH: Advanced mathematics
Why Benchmarks Matter: - Compare models objectively - Track progress over time - Identify strengths/weaknesses - Guide model selection
Limitations: - Gaming/overfitting possible - May not reflect real-world use - Quickly become saturated - Don't capture everything
Leaderboards: - Open LLM Leaderboard (Hugging Face) - Chatbot Arena (LMSYS) - HELM (Stanford)
Examples
GPT-4 scoring 86.4% on MMLU vs Claude 3 Opus at 86.8%.
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